整合基因组畸变,预测接受新辅助化疗的胃食管腺癌患者的临床预后

E.C. Smyth , D. Watson , M.P. Castro , B. Nutzinger , S. Kapoor , S. Rajagopalan , C. Cheah , P.R. Nair , A. Alam , G. Devonshire , N. Grehan , R.P. Suseela , A. Tyagi , A.K. Agrawal , M. Sauban , A. Pampana , A. Ghosh , Y. Ullal , Y. Narvekar , M.D. Macpherson , R.C. Fitzgerald
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引用次数: 0

摘要

背景食管癌[食管胃腺癌(OGA)]在分子水平上表现出异质性,导致有效率降低,突出了对个性化治疗策略的需求。我们开发了一个计算模型,利用机理和统计方法整合患者的基因组畸变,揭示信号通路失调和不同的药物反应。在这项研究中,模型输出结果--治疗反应指数(TRI)被用于预测疗效。设计TRI预测患者疗效的能力在英国食管癌临床和分子分层联合会(OCCAMS)前瞻性收集的接受新辅助化疗的可手术OGA患者队列中进行了回顾性评估。采用分层随机抽样将数据分为训练子集和验证子集。结果 共筛选出270名OGA患者,对活检或切除的组织进行了50×全基因组测序。患者根据英国临床指南接受化疗药物或方案治疗。TRI与总生存期(OS)的关系显著高于标准临床因素(P = 0.0012)。与无病生存期(DFS;P = 0.0288)也有明显关系。结论 TRI对OS和DFS的预测作用超出了临床因素。这些积极的结果表明,以生物模拟为依据的个性化疗法选择具有潜在的实用性,有必要在前瞻性临床研究中进行进一步评估。
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Integration of genomic aberrations to predict clinical outcomes for patients with gastroesophageal adenocarcinoma receiving neoadjuvant chemotherapy

Background

Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study.

Design

TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors.

Results

A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (P = 0.0012). A significant association was also observed with disease-free survival (DFS; P = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (P = 0.0011).

Conclusions

TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.

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